Examples of weka.core.TestInstances

weka.core.TestInstances

Generates artificial datasets for testing. In case of Multi-Instance data the settings for the number of attributes applies to the data inside the bag. Originally based on code from the CheckClassifier.

Valid options are:

 -relation <name> The name of the data set.

 -seed <num> The seed value.

 -num-instances <num> The number of instances in the datasets (default 20).

 -class-type <num> The class type, see constants in weka.core.Attribute (default 1=nominal).

 -class-values <num> The number of classes to generate (for nominal classes only) (default 2).

 -class-index <num> The class index, with -1=last, (default -1).

 -no-class Doesn't include a class attribute in the output.

 -nominal <num> The number of nominal attributes (default 1).

 -nominal-values <num> The number of values for nominal attributes (default 2).

 -numeric <num> The number of numeric attributes (default 0).

 -string <num> The number of string attributes (default 0).

 -words <comma-separated-list> The words to use in string attributes.

 -word-separators <chars> The word separators to use in string attributes.

 -date <num> The number of date attributes (default 0).

 -relational <num> The number of relational attributes (default 0).

 -relational-nominal <num> The number of nominal attributes in a rel. attribute (default 1).

 -relational-nominal-values <num> The number of values for nominal attributes in a rel. attribute (default 2).

 -relational-numeric <num> The number of numeric attributes in a rel. attribute (default 0).

 -relational-string <num> The number of string attributes in a rel. attribute (default 0).

 -relational-date <num> The number of date attributes in a rel. attribute (default 0).

 -num-instances-relational <num> The number of instances in relational/bag attributes (default 10).

 -multi-instance Generates multi-instance data.

 -W <classname> The Capabilities handler to base the dataset on. The other parameters can be used to override the ones determined from the handler. Additional parameters for handler can be passed on after the '--'.

@author FracPete (fracpete at waikato dot ac dot nz) @version $Revision: 6325 $ @see weka.classifiers.CheckClassifier

                                      int numString, int numDate,
                                      int numRelational,
                                      boolean multiInstance)
  throws Exception {
    
    TestInstances dataset = new TestInstances();
    
    dataset.setSeed(seed);
    dataset.setNumInstances(numInstances);
    dataset.setNumNominal(numNominal);
    dataset.setNumNumeric(numNumeric);
    dataset.setNumString(numString);
    dataset.setNumDate(numDate);
    dataset.setNumRelational(numRelational);
    dataset.setClassIndex(TestInstances.NO_CLASS);
    dataset.setMultiInstance(multiInstance);
    
    return dataset.generate();
  }

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                                      int numClasses, int classType,
                                      int classIndex,
                                      boolean multiInstance)
  throws Exception {
    
    TestInstances dataset = new TestInstances();
    
    dataset.setSeed(seed);
    dataset.setNumInstances(numInstances);
    dataset.setNumNominal(numNominal);
    dataset.setNumNumeric(numNumeric);
    dataset.setNumString(numString);
    dataset.setNumDate(numDate);
    dataset.setNumRelational(numRelational);
    dataset.setNumClasses(numClasses);
    dataset.setClassType(classType);
    dataset.setClassIndex(classIndex);
    dataset.setNumClasses(numClasses);
    dataset.setMultiInstance(multiInstance);
    dataset.setWords(getWords());
    dataset.setWordSeparators(getWordSeparators());
    
    return process(dataset.generate());
  }

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                                      int numClasses, int classType,
                                      int classIndex,
                                      boolean multiInstance)
  throws Exception {
    
    TestInstances dataset = new TestInstances();
    
    dataset.setSeed(seed);
    dataset.setNumInstances(numInstances);
    dataset.setNumNominal(numNominal);
    dataset.setNumNumeric(numNumeric);
    dataset.setNumString(numString);
    dataset.setNumDate(numDate);
    dataset.setNumRelational(numRelational);
    dataset.setNumClasses(numClasses);
    dataset.setClassType(classType);
    dataset.setClassIndex(classIndex);
    dataset.setNumClasses(numClasses);
    dataset.setMultiInstance(multiInstance);
    dataset.setWords(getWords());
    dataset.setWordSeparators(getWordSeparators());
    
    return process(dataset.generate());
  }

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                                      int numClasses, int classType,
                                      int classIndex,
                                      boolean multiInstance)
  throws Exception {
    
    TestInstances dataset = new TestInstances();
    
    dataset.setSeed(seed);
    dataset.setNumInstances(numInstances);
    dataset.setNumNominal(numNominal);
    dataset.setNumNumeric(numNumeric);
    dataset.setNumString(numString);
    dataset.setNumDate(numDate);
    dataset.setNumRelational(numRelational);
    dataset.setNumClasses(numClasses);
    if (classType == NO_CLASS) {
      dataset.setClassType(Attribute.NOMINAL);  // ignored
      dataset.setClassIndex(TestInstances.NO_CLASS);
    }
    else {
      dataset.setClassType(classType);
      dataset.setClassIndex(classIndex);
    }
    dataset.setNumClasses(numClasses);
    dataset.setMultiInstance(multiInstance);
    dataset.setWords(getWords());
    dataset.setWordSeparators(getWordSeparators());
    
    return process(dataset.generate());
  }

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                                      int numClasses, int classType,
                                      int classIndex,
                                      boolean multiInstance)
  throws Exception {
    
    TestInstances dataset = new TestInstances();
    
    dataset.setSeed(seed);
    dataset.setNumInstances(numInstances);
    dataset.setNumNominal(numNominal);
    dataset.setNumNumeric(numNumeric);
    dataset.setNumString(numString);
    dataset.setNumDate(numDate);
    dataset.setNumRelational(numRelational);
    dataset.setNumClasses(numClasses);
    dataset.setClassType(classType);
    dataset.setClassIndex(classIndex);
    dataset.setNumClasses(numClasses);
    dataset.setMultiInstance(multiInstance);
    dataset.setWords(getWords());
    dataset.setWordSeparators(getWordSeparators());
    
    return process(dataset.generate());
  }

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              int numAttr, AttrTypes attrTypes,
              int numClasses, int classType,
              int classIndex)
    throws Exception {
    
    TestInstances dataset = new TestInstances();
    
    dataset.setSeed(seed);
    dataset.setNumInstances(numInstances);
    dataset.setNumNominal   (attrTypes.nominal     ? numAttr : 0);
    dataset.setNumNumeric   (attrTypes.numeric     ? numAttr : 0);
    dataset.setNumString    (attrTypes.string      ? numAttr : 0);
    dataset.setNumDate      (attrTypes.date        ? numAttr : 0);
    dataset.setNumRelational(attrTypes.relational  ? numAttr : 0);
    dataset.setNumClasses(numClasses);
    dataset.setClassType(classType);
    dataset.setClassIndex(classIndex);
    
    return process(dataset.generate());
  }

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                                      int numClasses, int classType,
                                      int classIndex,
                                      boolean multiInstance)
  throws Exception {


    TestInstances dataset = new TestInstances();


    dataset.setSeed(seed);
    dataset.setNumInstances(numInstances);
    dataset.setNumNominal(numNominal);
    dataset.setNumNumeric(numNumeric);
    dataset.setNumString(numString);
    dataset.setNumDate(numDate);
    dataset.setNumRelational(numRelational);
    dataset.setNumClasses(numClasses);
    dataset.setClassType(classType);
    dataset.setClassIndex(classIndex);
    dataset.setNumClasses(numClasses);
    dataset.setMultiInstance(multiInstance);
    dataset.setWords(getWords());
    dataset.setWordSeparators(getWordSeparators());


    return process(dataset.generate());
  }

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              int numAttr, AttrTypes attrTypes,
              int numClasses, int classType,
              int classIndex)
    throws Exception {
    
    TestInstances dataset = new TestInstances();
    
    dataset.setSeed(seed);
    dataset.setNumInstances(numInstances);
    dataset.setNumNominal   (attrTypes.nominal     ? numAttr : 0);
    dataset.setNumNumeric   (attrTypes.numeric     ? numAttr : 0);
    dataset.setNumString    (attrTypes.string      ? numAttr : 0);
    dataset.setNumDate      (attrTypes.date        ? numAttr : 0);
    dataset.setNumRelational(attrTypes.relational  ? numAttr : 0);
    dataset.setNumClasses(numClasses);
    dataset.setClassType(classType);
    dataset.setClassIndex(classIndex);
    
    return process(dataset.generate());
  }

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  }
  
  protected Instances generateData(boolean nomClass, int numClasses, 
      int numNominal, int numNumeric) throws Exception {
    
    TestInstances generator = new TestInstances();
    
    if (nomClass) {
      generator.setClassType(Attribute.NOMINAL);
      generator.setNumClasses(numClasses);
    } else {
      generator.setClassType(Attribute.NUMERIC);
    }
    
    generator.setNumNominal(numNominal);
    generator.setNumNumeric(numNumeric);
    
    generator.setNumDate(0);
    generator.setNumString(0);
    generator.setNumRelational(0);
    generator.setNumInstances(100);
    
    generator.setClassIndex(TestInstances.CLASS_IS_LAST);
    Instances data = generator.generate();
        
    return data;
  }

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   * 
   * @return    the dataset for the FilteredClassifier
   * @throws Exception  if generation of data fails
   */
  protected Instances getFilteredClassifierData() throws Exception {
    TestInstances  test;
    Instances    result;


    // NB: in order to make sure that the classifier can handle the data,
    //     we're using the classifier's capabilities to generate the data.
    test = TestInstances.forCapabilities(
    m_FilteredClassifier.getClassifier().getCapabilities());
    test.setClassIndex(TestInstances.CLASS_IS_LAST);


    result = test.generate();
    
    return result;
  }

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weka.associations.CheckAssociator

weka.attributeSelection.CheckAttributeSelection

weka.classifiers.CheckClassifier

weka.classifiers.functions.supportVector.CheckKernel

weka.classifiers.misc.InputMappedClassifierTest

weka.classifiers.misc.SerializedClassifierTest

weka.clusterers.CheckClusterer

weka.core.converters.AbstractConverterTest

weka.estimators.CheckEstimator

weka.filters.AbstractFilterTest

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